Friday, March 30, 2012

"More concerning, say the editors, is that this trend may be a symptom of a growing dysfunction in the biomedical sciences, one that needs to be addressed soon. At the heart of the problem is an economic incentive system fueling a hypercompetitive environment that is fostering poor scientific practices, including frank misconduct."

Thursday, March 22, 2012

"Participants will undergo a one-time blood draw in order to test for zonulin concentration in serum (ng/mg) and these results will be compared to normative data to screen for elevations. The sample size for this pilot study was estimated based on the known prevalence of Celiac disease in schizophrenia, a disease known to have elevated zonulin levels."

Friday, March 16, 2012

Personally, I learned the most from just running in as little shoe (or no shoe) as I could get away with. Some of the running advice can be counterproductive. But I'm curious, so I've read about a bunch of these methods, and they all have interesting aspects...

"7) As I always consider conflict of interest, it would be remiss of me to end without noting that one of the authors (if not more) is known to be vegetarian and speaks at vegetarian conferences[ii] and the invited ‘peer’ review of the article has been done by none other than the man who claims the credit for having turned ex-President Clinton into a vegan – Dean Ornish.[iii]"

"...Lastly, although the authors included controls for lifestyle factors I’m highly suspicious that people with so many unhealthy habits are at an increased risk of death primarily because of meat consumption...."

And here's the real nail in the coffin for this bit of propaganda:

“They found that the FFQ predicted true intake of some foods very well and true intake of other foods very poorly. True intake of coffee could explain 55 percent of the variation in answers on the FFQ, while true intake of beer could explain almost 70 percent. True intake of skim milk and butter both explained about 45 percent, while eggs followed closely behind at 41 percent.

"But the ability of the FFQ to predict true intake of meats was horrible. It was only 19 percent for bacon, 14 percent for skinless chicken, 12 percent for fish and meat, 11 percent for processed meats, 5 percent for chicken with skin, 4 percent for hot dogs, and 1.4 percent for hamburgers."

"If your jaw just dropped, let me assure you that you read that right and it is not a typo. The true intake of hamburgers explained only 1.4 percent of the variation in people’s claims on the FFQ about how often they ate hamburgers!”"

"Stop for a moment and wrap your mind around this fact: the intake of meat reported by the hundreds of studies which use data mined from the Nurses’ Health Study is almost completely unrelated to how much meat the study participants actually ate."

"Back in 2007 when I first published Good Calories, Bad Calories I also wrote a cover story in the New York Times Magazine on the problems with observational epidemiology. The article was called “Do We Really Know What Makes Us Healthy?” and I made the argument that even the better epidemiologists in the world consider this stuff closer to a pseudoscience than a real science. I used as a case study the researchers from the Harvard School of Public Health, led by Walter Willett, who runs the Nurses’ Health Study. In doing so, I wanted to point out one of the main reasons why nutritionists and public health authorities have gone off the rails in their advice about what constitutes a healthy diet. The article itself pointed out that every time in the past that these researchers had claimed that an association observed in their observational trials was a causal relationship, and that causal relationship had then been tested in experiment, the experiment had failed to confirm the causal interpretation — i.e., the folks from Harvard got it wrong. Not most times, but every time. No exception. Their batting average circa 2007, at least, was .000.

Now it’s these very same Harvard researchers — Walter Willett and his colleagues — who have authored this new article claiming that red meat and processed meat consumption is deadly...

Read the whole thing.
P.P.S. Ned Kock, the "Health Correlator" and a professional statistician, has a slightly different take on this:

"I am not a big fan of using arguments such as “food questionnaires are unreliable” and “observational studies are worthless” to completely dismiss a study. There are many reasons for this. One of them is that, when people misreport certain diet and lifestyle patterns, but do that consistently (i.e., everybody underreports food intake), the biasing effect on coefficients of association is minor. Measurement errors may remain for this or other reasons, but regression methods (linear and nonlinear) assume the existence of such errors, and are designed to yield robust coefficients in their presence. Besides, for me to use these types of arguments would be hypocritical, since I myself have done several analyses on the China Study data (1), and built what I think are valid arguments based on those analyses...."

However he concludes:

"...But its magnitude is apparently greater than the reported effects of red meat on mortality, which are not only minute but may well be statistical artifacts."

"...In other words, certain stretches of DNA related to energy metabolism were "switched off" by methyl groups; a single hard workout removed these methyl groups to allow the genes to be expressed. This rapid change in DNA methylation is highly surprising -- scientists are only now beginning to figure out how these epigenetic mechanisms work. A further part of the study showed a dose-response effect: harder exercise produced more demethylation...."

The science of genetics is still a young one, and we're far from understanding how genes work. So if someone tells you "it's genetic", with the implication that there's nothing you can do about it, odds are they're likely wrong. There are many factors at work on our genes.

The fourth chair is reserved for Simon Bartold (Podiatrist, ASICS's Global Research Co-ordinator, former barefoot advocate turned maximalist) should he choose to emerge from his self-imposed exile from public debate to join us on the night.

Dr Daniel Green (Sports Scientist, Editor R4YL magazine) hopes to join us as our moderator for the evening and Dave Robertson (Physiotherapist, The Naked Runners) will be prowling the crowd with a microphone so you can join in the debate.

This isn't just an opportunity for the panel members to challenge each others positions, this is your opportunity to put your point of view and ask our panel members the hard questions! The panel will also be answering questions posed by guest experts from around the world including podiatrist and biomechanist Associate Professor Kevin Kirby and evolutionary biologist Dr Peter Larson of runblogger.com fame.

Thursday, March 8, 2012

"...How fast are the subjects? The 10 Kenyans, including Martin Lel (many-time New York and London marathon champ) and Sammy Korir (the guy who missed the marathon world record by one second in Berlin one year), have an average time of 2:07:17. The nine Europeans, including Olympic champ Stefano Baldini and World Championship medalist Viktor Rothlin, have an average time (for those who've run a marathon) of 2:08:24. The two groups were statistically indistinguishable in terms of running performance and physical characteristics like body weight...."

Emphasis mine. This is a fine example of the difference between "statistical significance", and significance in the real world. They don't give out gold medals on statistically significant finishes, but on who crosses the finish line first.

And yes, the answer to why the Kenyans are faster is in the article, but not in the statistics.

Monday, March 5, 2012

"...I've been following most of the recommendations on diet and barefoot-style
running for long enough (and before reading the book) that I'm a big fan. The
one part the book added for me was a detailed explanation of Dr. Phil's
180-formula for training intensity. I'm now using this as my guide, and have
definitely noticed benefits so far. It's not magic, but it's definitely
improved my training in the few months I've been using it. I hope to continue
through the winter, and start seeing the benefits of this approach come spring...."

I haven't followed his protocol diligently, except that I diligently did runs using his 180 formula. I also did some anaerobic mountain biking, one of which resulted in a pulled calf muscle that sidelined me for a couple of months. If I was diligent, I wouldn't have interspersed anaerobic activity in what I was hoping would be a base-building period. I never did a Maximum Aerobic Fitness test, as Maffetone suggests, for two reasons. One, I find the notion of testing and tracking my fitness annoying. Two, he suggests regular MAF tests to reassure you that you're making progress, since other evidence may be slim at first, and you may need some reassurance that you're improving. Since I buy into his approach whole-heartedly (so to speak), I didn't need the reassurance.

I decided this past weekend to do a long, slow run with the heart-rate monitor, to get back in the protocol. (Not up and down the mountain, this time.) I haven't used the HRM since the fall, and the strap appeared to be dead at the beginning of the run. Then I realized that I didn't really have enough time to do a long run. (No, this was not incredibly well planned...) So I decided to do a tempo run. As I was running along I noticed that the HRM was in fact working, as it was telling me that I was exceeding my MAF heart rate. Sigh; so I decided to continue at the tempo pace, and compare the results to the Paine to Pain (P2P) race I had done in October, since I had HR data from that race.

So here's the data, by mile:

Paine to Pain

Tempo

Mile

Pace

HR

Pace

HR

1

8:08.2

170

8:57.9

183

2

9:23.2

181

9:51.3

166

3

8:53.9

182

7:52.6

168

4

9:49.4

178

9:21.2

163

5

8:35.6

179

8:05.9

166

Now, there are a few caveats. First, the HRM was nonfunctional for some part of mile one, and seemed to start working by showing a rate of 199. So the HR data for mile one is useless. Second, I had my dog along on the tempo run, and he kept stopping to pee and other doggie business, which always messes up my pace, and causes my HR to rise. Third, the Tempo course had much steeper hills than the P2P course did. Mile 2 was partly a rough uphill trail section; mile 3 (I think) includes both a steep downhill and a 21% grade uphill that I ran at a heart rate of 180-181; and the end of mile 5 is also uphill.
But all those caveats should have made for a worse pace and HR, and for the most part, both were better. Much better. The usable HR data show an average improvement of 14 beats per minute. The pace data isn't really comparable, since the P2P data is from the first few miles of a longer run, but I'm still happy with it.

As I said at the opening, I'm surprised. I'd been under the impression, based on my runs in the fall prior to the injury, that Maffetone's protocol hadn't been working all that well for me. But clearly it has.

Perhaps the long break allowed for the physiological changes to occur, or perhaps it was just that I stopped watching the pot?

Sunday, March 4, 2012

"...A study led by Jonathan Tilly of the Massachusetts General Hospital overturns the decades-long idea that women are born with all the eggs they will ever have. It reports that women of reproductive age carry ovarian stem cells, meaning that they can produce new eggs.

So, to recap: after centuries of intensive scientific research we are still learning amazing and surprising things about our bodies...."

Yes, so they should stop telling us what to do until they know how things work.